The H.264 Advanced Video Coder (i.e., H.264) standard has introduced a state-of-the-art and high compression efficiency coding technique. High coding performance is made possible by implementing many tools, like flexible block size motion compensation, sub-pixel level motion compensation, bidirectional motion estimation, de-blocking filtering, flexible transforms and efficient entropy coding. The tools commonly consume significant computational power for processors utilized in the video coding.
From a perceptual performance point of view, coding whole images with the same quality is inefficient. A viewer attention model can be taken into consideration to improve an overall quality and/or reduce an output bandwidth for the same quality. From a computational complexity point of view, focusing the encoding on important parts of an image is beneficial. The image parts that receive special attention are called regions of interest (i.e., ROI). A conventional simple technique to detect an ROI uses a fixed area specified by the user. Other common techniques use more computationally complex approaches that involve face detection and edge detection.
It would be desirable to implement an efficient region of interest detection.